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DeepSeek V3 vs Switchyard
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Switchyard has about 6.1× the context window of the other in this pair.
Switchyard has 510% more context capacity (1000K vs 163K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Switchyard. Its 1000K context fits entire documents without chunking (vs 163K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | DeepSeek V3 | Switchyard |
|---|---|---|
| Context window | 163,840 tokens (163K) | 1,000,000 tokens (1000K) |
| Max output tokens | 163,840 tokens (163K) | N/A |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | Dec 2024 | Sep 2026 |
Frequently asked questions
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Example: a multi-turn chat session
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